Additive Models of Single-tree Biomass Sensitive to Temperature and Precipitation in Eurasia – A Comparative Study for Larix spp. and Quercus spp.

In the context of current climate change, it is important to know the patterns characterising the response of forest trees to the dynamics of air temperature and precipitation. In this study, the first attempt to model changes of additive component composition of genera Larix spp. and Quercus spp. aboveground biomass according to Eurasian gradients of January’s mean temperature and annual mean precipitation is made, taking into account regional particularities of tree age and morphology structure. In the process of modelling, the database of single-tree biomass for forest-forming species in Eurasia is used. According to our results, the factors limiting the biomass of trees differ not only between the two tree genera but also between different components of biomass within the genus. In larches, the reaction of the biomass of all components to an increase in precipitation in cold zones is directly opposite in comparison with oaks, i.e. it decreases as precipitation increases. But in warm areas, the reactions of the two genera to increased precipitation coincide, i.e. precipitation does not affect the biomass of all components, both in larches and oaks. In wet areas, larch biomass components react to temperature increases in the opposite way, i.e. the aboveground and stem biomass increases, but the biomass of foliage and branches decreases. In dry areas, the reaction to the temperature of all larch and oak biomass components is unambiguous and opposite, i.e. there is a decrease in the larch biomass of all components as temperatures rise, and in oak biomass vice versa. This situation is discussed in terms of limiting factors.

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Forest stand biomass of Picea spp.: an additive model that may be related to climate and civilisational changes

Bulletin of Geography. Socio-economic Series ◽

10.2478/bog-2019-0029 ◽

2019 ◽

Vol 45 (45) ◽

pp. 133-147 ◽

Cited By ~ 1

Author(s):

Vladimir А. Usoltsev ◽

Agnieszka Piernik ◽

Anna A. Osmirko ◽

Ivan S. Tsepordey ◽

Viktor P. Chasovskikh ◽

...

Keyword(s):

Climate Change ◽

Forest Cover ◽

General Pattern ◽

Additive Model ◽

Multivariate Regression Analysis ◽

Component Composition ◽

Mean Annual Precipitation ◽

Temperature And Precipitation ◽

Additive Component ◽

Biomass Components

AbstractSince ancient times, climate change has largely determined the fate of human civilisation, which was related mainly to changes in the structure and habitats of forest cover. In the context of current climate change, one must know the capabilities of forests to stabilise the climate by increasing biomass and carbon-depositing abilities. For this purpose, the authors compiled a database of harvest biomass (t/ha) in 900 spruce (Picea spp.) sample plots in the Eurasian area and used the methodology of multivariate regression analysis. The first attempt at modelling changes in the biomass additive component composition has been completed, according to the Trans-Eurasian hydrothermal gradients. It is found that the biomass of all components increases with the increase in the mean January temperature, regardless of mean annual precipitation. In warm zonal belts with increasing precipitation, the biomass of most of the components increases. In the process of transitioning from a warm zone to a cold one, the dependence of all biomass components upon precipitation is levelled, and at a mean January temperature of ˗30°C it becomes a weak negative trend. With an increase in temperature of 1°C in different ecoregions characterised by different values of temperature and precipitation, there is a general pattern of decrease in all biomass components. With an increase in precipitation of 100 mm in different ecoregions characterised by different values of temperature and precipitation, most of the components of biomass increase in warm zonal belts, and decrease in cold ones. The development of such models for the main forest-forming species of Eurasia will make it possible to predict changes in the productivity of the forest cover of Eurasia due to climate change.

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Additive model of aboveground biomass of larch single-trees related to age, Dbh and height, sensitive to temperature and precipitation in Eurasia

Journal of Applied Sciences and Environmental Management ◽

10.4314/jasem.v24i10.8 ◽

2020 ◽

Vol 24 (10) ◽

pp. 1759-1766

Author(s):

Vladimir А. Usoltsev ◽

Seyed Omid Reza Shobairi ◽

Anna. A. Osmirko ◽

Ivan. S. Tsepordey ◽

Viktor. P. Chasovskikh

Keyword(s):

Regression Models ◽

Forest Cover ◽

Additive Model ◽

Component Composition ◽

Mean Annual Precipitation ◽

Mean Annual Temperature ◽

Tree Biomass ◽

Temperature And Precipitation ◽

Additive Component ◽

The Mean

The first attempt of modeling changes in the aboveground additive component composition of larch (genus Larix spp.) tree biomass, according to the Trans-Eurasian hydrothermal gradients of Eurasia on the database compiled for the structure of harvest biomass in a number of 510 sample trees is fulfilled. The adequacy of the obtained regularities is determined by the level of variability 87-99 % explained by the proposed regression models. For the central territory of European Russia, characterized by the mean annual temperature of January -10 °C and the mean annual precipitation of 400 mm, the increase in temperature by 1°C at the constant level of precipitation causes on Larix spp. trees of the equal age and sizes, the decrease in the aboveground, stem, needle and branches by 0.4, 0.3, 1.4 и 1.3 %, respectively. For the same region, in equal-sized trees, the increase in precipitation by 100 mm at a constant annual temperature in January causes the decrease of the aboveground and stem biomass by 1.2 and 1.7%, respectively, and the increase of needle and branches biomass by 4.0 and 6.0%, respectively. The development of such models for the main forest-forming species of Eurasia will make it possible to predict changes in the productivity of the forest cover of Eurasia in connection with climate change. Keywords: larch trees, genus Larix spp., tree biomass, allometric models

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Fir (Abies spp.) stand biomass additive model for Eurasia sensitive to winter temperature and annual precipitation

Central European Forestry Journal ◽

10.2478/forj-2019-0017 ◽

2019 ◽

Vol 65 (3-4) ◽

pp. 166-179 ◽

Cited By ~ 3

Author(s):

Vladimir A. Usoltsev ◽

Katarína Merganičová ◽

Bohdan Konôpka ◽

Anna A. Osmirko ◽

Ivan S. Tsepordey ◽

...

Keyword(s):

Climate Change ◽

Biomass Allocation ◽

Aboveground Biomass ◽

Additive Model ◽

Tree Biomass ◽

Common Pattern ◽

Temperature And Precipitation ◽

Shoot Ratio ◽

Biomass Components ◽

Increasing Temperature

Abstract Climate change, especially modified courses of temperature and precipitation, has a significant impact on forest functioning and productivity. Moreover, some alterations in tree biomass allocation (e.g. root to shoot ratio, foliage to wood parts) might be expected in these changing ecological conditions. Therefore, we attempted to model fir stand biomass (t ha−1) along the trans-Eurasian hydrothermal gradients using the data from 272 forest stands. The model outputs suggested that all biomass components, except for the crown mass, change in a common pattern, but in different ratios. Specifically, in the range of mean January temperature and precipitation of −30°C to +10°C and 300 to 900 mm, fir stand biomass increases with both increasing temperature and precipitation. Under an assumed increase of January temperature by 1°C, biomass of roots and of all components of the aboveground biomass of fir stands increased (under the assumption that the precipitation level did not change). Similarly, an assumed increase in precipitation by 100 mm resulted in the increased biomass of roots and of all aboveground components. We conclude that fir seems to be a perspective taxon from the point of its productive properties in the ongoing process of climate change.

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Increasing contribution of climate variables to the explanation of Quercus spp. single-tree biomass variability in Eurasia as related to model deviation from allometry

Известия СПбЛТА ◽

10.21266/2079-4304.2020.233.39-59 ◽

2020 ◽

pp. 39-59

Author(s):

В.А. Усольцев ◽

В.Ф. Ковязин ◽

И.С. Цепордей

Keyword(s):

Structural Characteristics ◽

Tree Height ◽

Mirror Image ◽

Climate Variables ◽

Climate Trends ◽

Tree Biomass ◽

Independent Variables ◽

Single Tree ◽

Quercus Spp ◽

Biomass Variability

Лесные экосистемы, являясь поглотителями атмосферного углерода, играют важную роль в сокращении выбросов CO2 и предотвращении потепления климата. Авторы попытались смоделировать биомассу модельных деревьев Quercus L.,используя данные 500 деревьев, распределенных вдоль транс-евразийских гидротермических градиентов. На сегодняшний день предложено несколько моделей биомассы деревьев и древостоев, включающих в качестве независимых переменных как их морфолого-структурные характеристики, так и климатические показатели. Существующие модели позволяют прогнозировать изменения биомассы вследствие сдвигов климатических трендов, но не показывают вклада климатических переменных в объяснение изменчивости биомассы, которая зависит как от вида дерева и древостоя, так и от структуры модели. Разработанные модели показывают, в какой степени отклонение от классической аллометрической модели, вызванное включением дополнительных независимых переменных, увеличивает вклад климатических переменных в объяснение изменчивости биомассы. Этот вклад наибольший, когда модель включает возраст, диаметр ствола, высоту дерева и их совокупный эффект. 3D-интерпретация«лучшей» модели показала пропеллеро-образную зависимость компонентов биомассы дуба от температуры и осадков, форма которой является зеркальным отражением аналогичной зависимости для биомассы деревьев двухвойных сосен и лиственниц. Это может быть связано с особенностями функционирования лиственных и хвойных видов. Forest ecosystems, as sinks of atmospheric carbon, play an important role in reducing CO2 emissions and preventing annual temperatures from rising. We attempted to model Quercus spp. single-tree biomass using the data from 500 sample trees distributed along the trans-Eurasian hydrothermal gradients. Today, several models of the biomass of trees and stands have been proposed, including both morphological-structural characteristics of trees and stands, and climate indicators as independent variables. The models make it possible to predict changes in biomass due to shifts in climate trends, but do not show the contribution of climate variables to the explanation of biomass variability, which depends on both the species of the tree and stand, and the structure of a model. The models designed show to what extent the deviation from the classical allometric model caused by the inclusion of additional independent variables, increases the contribution of climate variables to the explanation of biomass variability. The model shows the greatest contribution when itincludes age, stem diameter, tree height, and their combined effect. The 3D- interpretation of the «best» model showed a propeller-shaped dependence of the components of oak tree biomass on temperatures and precipitation, the shape of which is a mirror image of a similar dependence for the biomass of trees of two-needled pines and larches. This may be due to the functioning traits of leaved and coniferous species.

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The Modeling and Forecasting of Carabid Beetle Distribution in Northwestern China

Insects ◽

10.3390/insects12020168 ◽

2021 ◽

Vol 12 (2) ◽

pp. 168

Author(s):

Xueqin Liu ◽

Hui Wang ◽

Dahan He ◽

Xinpu Wang ◽

Ming Bai

Keyword(s):

Generalized Additive Models ◽

Additive Models ◽

Carabid Beetle ◽

Conservation Strategies ◽

Environmental Predictors ◽

Temperate Steppe ◽

Temperature And Precipitation ◽

Steppe Ecosystems ◽

Modeling And Forecasting ◽

Richness Patterns

Beetles are key insect species in global biodiversity and play a significant role in steppe ecosystems. In the temperate steppe of China, the increasing degeneration of the grasslands threatens beetle species and their habitat. Using Generalized Additive Models (GAMs), we aimed to predict and map beetle richness patterns within the temperate steppe of Ningxia (China). We tested 19 environmental predictors including climate, topography, soil moisture and space as well as vegetation. Climatic variables (temperature, precipitation, soil temperature) consistently appeared among the most important predictors for beetle groups modeled. GAM generated predictive cartography for the study area. Our models explained a significant percentage of the variation in carabid beetle richness (79.8%), carabid beetle richness distribution seems to be mainly influenced by temperature and precipitation. The results have important implications for management and conservation strategies and also provides evidence for assessing and making predictions of beetle diversity across the steppe.

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Additivity of tree biomass components using ratio estimate

Anais da Academia Brasileira de Ciências ◽

10.1590/0001-3765201920180272 ◽

2019 ◽

Vol 91 (3) ◽

Author(s):

SYLVIO PÉLLICO NETTO ◽

ALEXANDRE BEHLING

Keyword(s):

Tree Biomass ◽

Ratio Estimate ◽

Biomass Components

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Statistical downscaling of a climate simulation of the last glacial cycle: temperature and precipitation over Northern Europe

Climate of the Past ◽

10.5194/cp-10-1489-2014 ◽

2014 ◽

Vol 10 (4) ◽

pp. 1489-1500 ◽

Cited By ~ 4

Author(s):

N. Korhonen ◽

A. Venäläinen ◽

H. Seppä ◽

H. Järvinen

Keyword(s):

Large Scale ◽

Climate Model ◽

Ice Sheet ◽

Additive Models ◽

Northern Europe ◽

Glacial Cycle ◽

Explanatory Variables ◽

Last Glacial ◽

Temperature And Precipitation ◽

The Last Glacial

Abstract. Earth system models of intermediate complexity (EMICs) have proven to be able to simulate the large-scale features of glacial–interglacial climate evolution. For many climatic applications the spatial resolution of the EMICs' output is, however, too coarse, and downscaling methods are needed. In this study we introduce a way to use generalized additive models (GAMs) for downscaling the large-scale output of an EMIC in very different climatological conditions ranging from glacial periods to current relatively warm climates. GAMs are regression models in which a combination of explanatory variables is related to the response through a sum of spline functions. We calibrated the GAMs using observations of the recent past climate and the results of short time-slice simulations of glacial climate performed by the relatively high-resolution general circulation model CCSM (Community Climate System Model) and the regional climate model RCA3 (Rossby Centre regional Atmospheric climate model). As explanatory variables we used the output of a simulation by the CLIMBER-2 (CLIMate and BiosphERe model 2) EMIC of the last glacial cycle, coupled with the SICOPOLIS (SImulation COde for POLythermal Ice Sheets) ice sheet model, i.e. the large-scale temperature and precipitation data of CLIMBER-2, and the elevation, distance to ice sheet, slope direction and slope angle from SICOPOLIS. The fitted GAMs were able to explain more than 96% of the temperature response with a correlation of >0.98 and more than 59% of the precipitation response with a correlation of >0.72. The first comparison with two pollen-based reconstructions of temperature for Northern Europe showed that CLIMBER-2 data downscaled by GAMs corresponded better with the reconstructions than did the bilinearly interpolated CLIMBER-2 surface temperature.

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Using linear mixed model and dummy variable model approaches to construct compatible single-tree biomass equations at different scales – A case study for Masson pine in Southern China

Journal of Forest Science ◽

10.17221/69/2011-jfs ◽

2012 ◽

Vol 58 (No. 3) ◽

pp. 101-115 ◽

Cited By ~ 16

Author(s):

L.Y. Fu ◽

W.S. Zeng ◽

S.Z. Tang ◽

R.P. Sharma ◽

H.K. Li

Keyword(s):

Mixed Model ◽

Linear Mixed Model ◽

Southern China ◽

Forest Biomass ◽

Tree Biomass ◽

Variable Model ◽

Masson Pine ◽

Dummy Variable ◽

Single Tree ◽

Biomass Models

The estimation of forest biomass is important for practical issues and scientific purposes in forestry. The estimation of forest biomass on a large-scale level would be merely possible with the application of generalized single-tree biomass models. The aboveground biomass data on Masson pine (Pinus massoniana) from nine provinces in southern China were used to develop generalized single-tree biomass models using both linear mixed model and dummy variable model methods. An allometric function requiring only diameter at breast height was used as a base model for this purpose. The results showed that the aboveground biomass estimates of individual trees with identical diameters were different among the forest origins (natural and planted) and geographic regions (provinces). The linear mixed model with random effect parameters and dummy model with site-specific (local) parameters showed better fit and prediction performance than the population average model. The linear mixed model appears more flexible than the dummy variable model for the construction of generalized single-tree biomass models or compatible biomass models at different scales. The linear mixed model method can also be applied to develop other types of generalized single-tree models such as basal area growth and volume models.  

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